A comprehensive study of the theory and application to biomedical research of Receiver Operating Characteristic (ROC) curves has continued. ROC analysis is used to compare two diagnostic tests via ROC area when the data are ordinal categories rather than continuous variables. Also, the theory of ROC curves has been extended to fuzzy data; instead of knowing that a patient is diseased or nondiseased, it is sometimes useful to view the patients's disease state to be a continuous variable between zero and one, where zero indicates normal and one indicates diseased. A study of the applicability of Lomax distribution to ROC curves has continued. A paper on the maximum likelihood estimation of Lomax models and their iterative fit via computer has been submitted. An important practical area of ROC analysis recently studied is the incorporation of covariate information. A collaboration joint with J. Malley, D. Levy and J. Bailey is using age and body mass index (habitus) in a linear regression model tim improve fuzzy ROC performance of an ECG test in prediction of left ventricular hypertrophy.